Generally, encoding is a process that a transmitting side performs a data processing for a receiving side to restore original data despite errors caused by signal distortion, signal loss and the like while the transmitting side transmits data via a communication channel. And, decoding is a process that the receiving side restores the encoded transmitted data into the original data.
Recently, many attentions are paid to an encoding method using an LPDC code. The LDPC code is a linear block code having low density since most of elements of a parity check matrix H are zeros, which was proposed by Gallager in 1962. It was difficult to implement the LDPC code that is very complicated due to the technological difficulty in those days. Yet, the LDPC code was taken into re-consideration in 1995 so that its superior performance has been verified. So, many efforts are made to research and develop the LPDC code. (Reference: [1] Robert G. Gallager, “Low-Density Parity-Check Codes”, The MIT Press, Sep. 15, 1963. [2] D. J. C. Mackay, Good error-correcting codes based on very sparse matrices, IEEE Trans. Inform. Theory, IT-45, pp. 399-431 (1999))
A parity check matrix of the LDPC code is a binary matrix including ‘0’ and ‘1’. Since the number of ‘1’ of the parity check matrix of the LDPC code is very small, decoding of the parity check matrix of the LDPC is enabled through repetition decoding in case of a large matrix size. If the matrix size is very large, the parity check matrix of the LDPC code shows performance approximating a channel capacity limit of Shannon like a turbo code.
The LDPC code can be explained by a parity check matrix H of (n−k)×n dimensions. And, a generator matrix G corresponding to the parity check matrix H can be found by Equation 1.H·G=0  [Equation 1]
In an encoding/decoding method using an LDPC code, a transmitting side encodes input data by Equation 2 using the generator matrix G having a relation of Equation 1 with the parity check matrix H.c=G·u, where ‘c’ is a codeword and ‘u’ is a data frame.  [Equation 2]
Yet, an input data encoding method using the parity check matrix H instead of using the generator matrix G is generally used nowadays. Hence, as explained in the above explanation, the parity check matrix H is the most important factor in the encoding/decoding method using the LDPC code. Since the parity check matrix H has a huge size, many operations are required for the corresponding encoding and decoding processes. And, implementation of the parity check matrix H is very complicated. Moreover, the parity check matrix H needs a large storage space.
In adding many weights to the parity check matrix H of the binary matrix including ‘0’ and ‘1’ (i.e., increasing the number of ‘1’), more variables are added to parity check equations. Hence, better performance can be shown in the encoding and decoding method using the LDPC code.
However, if more weights are added to the parity check matrix H, a 4-cycle or 6-cycle can be generated from the entire parity check matrix. Hence, the performance of the encoding and decoding method using the LDPC code may be degraded.
Moreover, a mobile communication system, wireless Internet system or the like frequently employs a variable data rate according to a channel status or a data volume to be transmitted. Yet, the related art encoding method using the LDPC has difficulty in being applied to the system employing the variable data rate.